Skip to content

Commit

Permalink
fix readme
Browse files Browse the repository at this point in the history
  • Loading branch information
@christopherkenny
christopherkenny committed Mar 22, 2024
1 parent 1579310 commit db9d73b
Show file tree
Hide file tree
Showing 2 changed files with 78 additions and 36 deletions.
10 changes: 8 additions & 2 deletions README.Rmd
View file
Original file line number Diff line number Diff line change
Expand Up @@ -16,7 +16,13 @@ knitr::opts_chunk$set(
# cvap <a href='https://christophertkenny.com/cvap/'><img src='man/figures/logo.png' align="right" height="138" /></a>

<!-- badges: start -->
[![R-CMD-check](https://github.com/christopherkenny/cvap/workflows/R-CMD-check/badge.svg)](https://github.com/christopherkenny/cvap/actions)
[![CRAN
status](https://www.r-pkg.org/badges/version/cvap)](https://CRAN.R-project.org/package=cvap)
[![cvap status
badge](https://christopherkenny.r-universe.dev/badges/cvap)](https://christopherkenny.r-universe.dev/cvap)
[![Lifecycle:
stable](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html#stable)
[![R-CMD-check](https://github.com/christopherkenny/cvap/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/christopherkenny/cvap/actions/workflows/R-CMD-check.yaml)
<!-- badges: end -->

The goal of `cvap` is to work with Census citizen voting-age population (CVAP) data.
Expand Down Expand Up @@ -68,7 +74,7 @@ data('de_block_group')

This allows us to distribute the block group data approximately between blocks.
```{r}
block_est <- cvap_distribute(de_cvap, de_block, de_block_group)
block_est <- cvap_distribute(de_cvap, de_block_group)
```


Expand Down
104 changes: 70 additions & 34 deletions README.md
View file
Original file line number Diff line number Diff line change
@@ -1,12 +1,18 @@

<!-- README.md is generated from README.Rmd. Please edit that file -->

# cvap
\# cvap
<a href='https://christophertkenny.com/cvap/'><img src='man/figures/logo.png' align="right" height="138" /></a>

<!-- badges: start -->

[![R-CMD-check](https://github.com/christopherkenny/cvap/workflows/R-CMD-check/badge.svg)](https://github.com/christopherkenny/cvap/actions)
[![CRAN
status](https://www.r-pkg.org/badges/version/cvap)](https://CRAN.R-project.org/package=cvap)
[![cvap status
badge](https://christopherkenny.r-universe.dev/badges/cvap)](https://christopherkenny.r-universe.dev/cvap)
[![Lifecycle:
stable](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html#stable)
[![R-CMD-check](https://github.com/christopherkenny/cvap/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/christopherkenny/cvap/actions/workflows/R-CMD-check.yaml)
<!-- badges: end -->

The goal of `cvap` is to work with Census citizen voting-age population
Expand Down Expand Up @@ -68,7 +74,26 @@ This allows us to distribute the block group data approximately between
blocks.

``` r
block_est <- cvap_distribute(de_cvap, de_block, de_block_group)
block_est <- cvap_distribute(de_cvap, de_block_group)
#> New names:
#> • `cvap` -> `cvap...21`
#> • `cvap_white` -> `cvap_white...22`
#> • `cvap_black` -> `cvap_black...23`
#> • `cvap_hisp` -> `cvap_hisp...24`
#> • `cvap_aian` -> `cvap_aian...25`
#> • `cvap_asian` -> `cvap_asian...26`
#> • `cvap_nhpi` -> `cvap_nhpi...27`
#> • `cvap_other` -> `cvap_other...28`
#> • `cvap_two` -> `cvap_two...29`
#> • `cvap` -> `cvap...31`
#> • `cvap_white` -> `cvap_white...32`
#> • `cvap_black` -> `cvap_black...33`
#> • `cvap_hisp` -> `cvap_hisp...34`
#> • `cvap_asian` -> `cvap_asian...35`
#> • `cvap_aian` -> `cvap_aian...36`
#> • `cvap_nhpi` -> `cvap_nhpi...37`
#> • `cvap_two` -> `cvap_two...38`
#> • `cvap_other` -> `cvap_other...39`
```

This workflow can also be combined into one function
Expand All @@ -81,37 +106,48 @@ The resulting data has estimated CVAP data for each block:

``` r
dplyr::glimpse(block_est)
#> Rows: 24,115
#> Columns: 29
#> $ GEOID <chr> "100010401001000", "100010401001001", "100010401001002", "1~
#> $ NAME <chr> "Block 1000, Block Group 1, Census Tract 401, Kent County, ~
#> $ pop <dbl> 77, 294, 20, 91, 53, 6, 50, 0, 0, 21, 294, 19, 0, 23, 42, 0~
#> $ pop_white <dbl> 53, 280, 20, 91, 50, 6, 47, 0, 0, 19, 261, 18, 0, 23, 41, 0~
#> $ pop_black <dbl> 9, 5, 0, 0, 0, 0, 3, 0, 0, 0, 19, 1, 0, 0, 1, 0, 1, 0, 0, 1~
#> $ pop_hisp <dbl> 9, 3, 0, 0, 3, 0, 0, 0, 0, 0, 8, 0, 0, 0, 0, 0, 0, 0, 0, 7,~
#> $ pop_aian <dbl> 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,~
#> $ pop_asian <dbl> 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,~
#> $ pop_nhpi <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,~
#> $ pop_other <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,~
#> $ pop_two <dbl> 4, 5, 0, 0, 0, 0, 0, 0, 0, 2, 4, 0, 0, 0, 0, 0, 2, 0, 0, 0,~
#> $ vap <dbl> 48, 223, 12, 64, 44, 6, 42, 0, 0, 14, 203, 13, 0, 13, 30, 0~
#> $ vap_white <dbl> 36, 214, 12, 64, 42, 6, 40, 0, 0, 13, 179, 12, 0, 13, 29, 0~
#> $ vap_black <dbl> 4, 4, 0, 0, 0, 0, 2, 0, 0, 0, 14, 1, 0, 0, 1, 0, 1, 0, 0, 1~
#> $ vap_hisp <dbl> 5, 1, 0, 0, 2, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 2,~
#> $ vap_aian <dbl> 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,~
#> $ vap_asian <dbl> 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,~
#> $ vap_nhpi <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,~
#> $ vap_other <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,~
#> $ vap_two <dbl> 1, 3, 0, 0, 0, 0, 0, 0, 0, 1, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0,~
#> $ cvap <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,~
#> $ cvap_white <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,~
#> $ cvap_black <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,~
#> $ cvap_hisp <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,~
#> $ cvap_asian <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,~
#> $ cvap_aian <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,~
#> $ cvap_nhpi <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,~
#> $ cvap_two <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,~
#> $ cvap_other <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,~
#> Rows: 574
#> Columns: 40
#> $ GEOID <chr> "100030101042", "100010412002", "100010411002", "10001…
#> $ NAME <chr> "Block Group 2, Census Tract 101.04, New Castle County…
#> $ pop <dbl> 1909, 2595, 1068, 2852, 0, 473, 63, 35, 53, 781, 57, 2…
#> $ pop_white <dbl> 1006, 1067, 713, 1986, 0, 459, 56, 35, 51, 745, 57, 26…
#> $ pop_black <dbl> 629, 932, 94, 297, 0, 0, 0, 0, 0, 20, 0, 0, 0, 278, 73…
#> $ pop_hisp <dbl> 244, 103, 242, 451, 0, 7, 7, 0, 0, 5, 0, 6, 0, 240, 95…
#> $ pop_aian <dbl> 0, 0, 0, 35, 0, 0, 0, 0, 0, 0, 0, 0, 0, 28, 0, 0, 0, 0…
#> $ pop_asian <dbl> 0, 376, 4, 8, 0, 7, 0, 0, 2, 4, 0, 0, 0, 488, 74, 0, 0…
#> $ pop_nhpi <dbl> 0, 19, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
#> $ pop_other <dbl> 0, 16, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
#> $ pop_two <dbl> 30, 82, 10, 75, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 77, 0, 0…
#> $ vap <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ vap_white <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ vap_black <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ vap_hisp <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ vap_aian <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ vap_asian <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ vap_nhpi <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ vap_other <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ vap_two <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ cvap...21 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ cvap_white...22 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ cvap_black...23 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ cvap_hisp...24 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ cvap_aian...25 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ cvap_asian...26 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ cvap_nhpi...27 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ cvap_other...28 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ cvap_two...29 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
#> $ bg_GEOID <chr> "100030101042", "100010412002", "100010411002", "10001…
#> $ cvap...31 <dbl> 1120, 805, 0, 0, 0, 545, 155, 20, 35, 710, 250, 350, 2…
#> $ cvap_white...32 <dbl> 630, 415, 0, 0, 0, 535, 150, 20, 30, 605, 250, 270, 25…
#> $ cvap_black...33 <dbl> 350, 150, 0, 0, 0, 0, 0, 0, 0, 15, 0, 0, 0, 140, 0, 0,…
#> $ cvap_hisp...34 <dbl> 120, 15, 0, 0, 0, 4, 4, 0, 4, 15, 0, 4, 0, 265, 310, 0…
#> $ cvap_asian...35 <dbl> 0, 35, 0, 0, 0, 4, 0, 0, 4, 4, 0, 0, 0, 45, 0, 0, 195,…
#> $ cvap_aian...36 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 75, 0, 4, 0, 10, 0, 0, 0, 0…
#> $ cvap_nhpi...37 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
#> $ cvap_two...38 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 40, 0,…
#> $ cvap_other...39 <dbl> 20, 190, 0, 0, 0, 2, 1, 0, 0, 0, 0, 72, 0, 45, 0, 0, 2…
#> $ impl_cvap <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
```

Thus, using other packages like `PL94171`, we can easily aggregate this
Expand Down

0 comments on commit db9d73b

Please sign in to comment.